tbuckley/cabot-search huggingface dataset:
Abstract 13585: In Patients With Right Bundle Branch Block, ECG Z-Axis QRS-T Voltage-Time-Integral Predicts Right Ventricular Structure and Function
Authors: Tyan Fairbank, Ashley DeBauge, Christopher J Harvey, Sagar Ranka, Sania Jiwani, Seth H Sheldon, Madhu Reddy, Timothy A Beaver, Amit Noheria
Journal: Circulation (2022)

Introduction: Right bundle branch block (RBBB) is the most common His-Purkinje conduction abnormality seen on ECG. It is currently unclear if there are any quantitative ECG differences in RBBB without and with structural right ventricular (RV) disease. Our aim was to evaluate quantitative ECG predictors of echocardiographic RV measurements [tricuspid annular plane systolic excursion (TAPSE), tissue Doppler imaging RV S’, RV basal and mid diameters, RV systolic pressure (RVSP)]. Hypothesis: QRS-T VTI in patients with RBBB is a marker for adverse RV remodeling and dysfunction. Methods: We included adults with ECG demonstrating typical RBBB and echocardiogram performed within 3 months of each other in 2010-2020. Orthogonal X, Y, Z ECG leads were reconstructed using Kors matrix. In addition to overall QRS duration, QRS voltages and QRS/QRS-T VTIs from 12 standard leads, X, Y, Z leads, and 3D (root-mean-square) ECG were evaluated. Age, sex and BSA-adjusted linear regressions were used to assess associations between ECG variables and RV measurements. We separately generated ROC curves for predicting abnormal RV measurements from ECG variables. Results: We included 782 patients (33% women, 71±14 years). Amongst the ECG variables, BSA-indexed Z-axis QRS-T VTI (VTI QRST-Z *√BSA) was the strongest independent predictor of all 5 RV measurements (Table 1a shows a comparison of QRS duration, Z-axis amplitude and VTI). VTI QRST-Z *√BSA cutoff 62 μVsm had a sensitivity 62.7% and specificity 65.7% to distinguish presence of ≥3 abnormal out of the 5 RV measurements (Table 1b). Conclusions: Adverse RV remodeling causes augmentation of the anterior-posteriorly directed QRS-T potential which is seen as a change in Z-axis VTI. VTI QRST-Z *√BSA could be used as a marker for right heart failure in patients with RBBB.
Abstract 13183: Effectiveness of a Telehealth-Based Behavioral Lifestyle Program for Hypertension Control in African Americans: Results From Heals Med-Tech Randomized Controlled Study
Authors: Amanda Clarke, Ismail EL Moudden, LaWanda Wood, Olivia Newby, Sunita Dodani
Journal: Circulation (2022)

Background: Hypertension (HTN) is a great concern because of its widespread prevalence, and associated racial health disparities. HTN is higher among African Americans (AAs) than whites. Among the many barriers to control HTN is poor adherence to needed lifestyle changes. The efficacy-tested HEALS Med-Tech behavioral lifestyle HTN control program may provide some solutions. We present the findings from the 1-year HEALS Med-Tech program in AAs. Methods: This is a randomized control community trial implemented in a primary care setting. HEALS Med-Tech program includes a) HEALS (Healthy Eating and Living Spiritually), a 12-month program modified from DASH and PREMIER programs; b) Med-component provides medications and social support; and c) Tech-component provides interactive telehealth contact. Primary outcomes of interest is change in systolic BP (SBP). Mixed Model repeated measure method was used for outcome analysis. Results: 61 participants (50 females, 11 males) were enrolled and randomized to either HEALS Med-Tech or standard care (control). Participants’ mean age is 62.8 ± 10.8 years, majority (90%) had a family history of CVD and 26.5% had diabetes. At the baseline, the SBP was 139.52 mmHg and 146 mmHg for the HEALS and control groups, respectively (Figure 1), which significantly reduced after 1 year (p=0.0134) in HEALS group. Similarly, the DBP was 82.78 mmHg and 84.32 mmHg for HEALS and control groups, respectively, at the baseline (not shown). For DBP and SBP, the results showed a significant difference between the HEALS and Control groups at 6 and 12 weeks. Conclusion: HEALS Med-Tech behavioral lifestyle program could serve as an effective and sustainable model for BP among marginalized AAs. There is a need for implementation studies of longer duration, such as HEALS Med-Tech, to address social determinants for the programs to be sustainable. Further research is needed to explore the potential implementation of HEALS Med-Tech program into clinical practice.
Abstract 13612: Using Pre-Operative Cardiac Computed Tomography and Echocardiography to Predict New-Onset Atrial Fibrillation Following TAVR
Authors: Mark S Brahier, Shwetha Kochi, Julia Huang, Emma Piliponis, Andrew Smith, Adam Johnson, Suraya Poian, Musa Abdulkareem, Xiaoyang Ma, Colin Wu, Athanasios X Thomaides, Ron Waksman, Lowell Satler, Peter J Bergquist, Monvadi B Srichai, Steffen E Petersen, Jose D Vargas
Journal: Circulation (2022)

Introduction: New-onset atrial fibrillation (NOAF) following transcatheter aortic valve replacement (TAVR) has been associated with higher morbidity and mortality. Numerous studies have focused on clinical variables for NOAF prediction. In this study, we examine pre-operative cardiac computed tomography (cCT) and echocardiographic measurements for NOAF prediction following TAVR. Methods: This retrospective study includes 939 patients without pre-existing atrial fibrillation who underwent transfemoral TAVR between 2015 and 2020. Clinical data and standard pre-operative echocardiographic and cCT measurements were recorded. A machine learning method was used to derive left atrial volume and measures of epicardial adipose tissue from cCT. NOAF by 30-days was determined based on continuous electrocardiographic monitoring prior to hospital discharge and routine ECG at 2 and 4 weeks following TAVR. In a two-step analysis, random survival forest (RSF) was used to select variables of highest importance to NOAF prediction without assuming statistical models, followed by logistic regression analysis of the selected variables. Results: Among 939 patients, 47 (5%) experienced NOAF. Patients with NOAF had larger left atrial volume index (68.11 vs 56.96 cm 3 /kg/m 2 ; p&lt;0.001) but similar epicardial adipose tissue volume (71.78 vs 70.98 cm 3 ; p&gt;0.1) and epicardial adipose tissue attenuation (-81.16 vs -82.77 Hounsfield Units; p&gt;0.1). Among 28 covariates selected by RSF for variable importance, 4 covariates were predictive of NOAF in the multivariable logistic regression, including sinotubular junction short axis &gt;34mm [OR 5.687 (2.271-14.241); p=0.0002], maximum aortic valve pressure gradient [OR 1.037 (1.004-1.072); p=0.0266], mean aortic valve pressure gradient [OR 0.939 (0.894-0.986); p=0.0115], and body mass index &lt; 22kg/m 2 [OR 0.331 (0.150-0.729); p=0.006]. Model concordance was 0.75. Conclusions: Pre-operative cardiac computed tomography and echocardiographic measurements including sinotubular junction enlargement and aortic valve pressure gradient predict new-onset atrial fibrillation following TAVR.
Abstract 13292: Rural-Urban Differences in Mortality Rate of Myocardial Infarction and Heart Failure: A Systematic Review and Meta-Analysis
Authors: Mohammed Shurrab, Dennis T Ko, Rony Atoui, Atilio Costa Vitali, Raed Abu Shama, Sami alnasser, Rashmi Narendrula, Gregory Papadopoulos, Mary Catherine Kerr, Sarah McIsaac, Husam Abdel Qadir, Jeff S Healey, Mark Henderson
Journal: Circulation (2022)

Introduction: Studies indicate that living in a rural area may be associated with worse health outcomes. However, it is unclear whether rurality is associated with mortality in patients with acute myocardial infarction (AMI) and heart failure (HF). This systematic review and meta-analysis aimed to evaluate rural-urban differences in mortality rate after AMI or HF. Methods: A systematic search was conducted for studies published till May 1, 2022 in PubMed, Embase and CENTRAL. Included studies compared mortality rates after hospital admission for AMI or HF in rural versus urban areas. Follow up ranged between 30 days and 3 years. Adjusted Odds ratios (aORs) were pooled with a random-effects model. Results: Six cohort studies were identified, which included 785,156 patients (128,990 in rural vs. 656,166 in urban) with AMI and 1,159,000 patients (192,749 in rural vs. 966,251 in urban) with HF. Compared with urban, patients admitted with AMI in rural areas had higher mortality rates (16% vs 14%, aOR 1.12, 95% Confidence Interval (CI) 1.05-1.20; p =0.0003, I 2 =75%). Compared with urban, patients admitted with HF in rural areas had higher mortality rates (21% vs 18%, aOR 1.19, 95% CI 1.03-1.38; p =0.02, I 2 =90%). (Figure) Conclusions: Among patients with AMI or HF, living in rural areas is associated with an increased risk of mortality. Clinical and policy efforts are needed in order to reduce disparities in rural health.
Abstract 13318: Shared Genetic Architecture of RV-PA Coupling and Measures of Adiposity
Authors: Vineet Agrawal, Minoo Bagheri, Nataraja Sarma S Vaitinadin, Mingjian Shi, Jane F Ferguson, Quinn Wells, Deepak Gupta, Anna R Hemnes, Jonathan Mosley, Evan Brittain
Journal: Circulation (2022)

Introduction: The right ventricle’s ability to adapt to load stress, termed RV-PA coupling, is a major determinant of survival in pulmonary hypertension. However, the etiologic drivers of impaired RV-PA coupling are incompletely understood. One approach to identifying etiologic factors is through the study of the genetic architecture underlying impaired RV-PA coupling. We previously showed shared genetic risk between adiposity and RV size. Thus, we interrogated a polygenic predictor of RV-PA coupling to determine whether it shares genetic risk with adiposity. Methods: In 3493 adult subjects of European ancestry in Vanderbilt Univ. Medical Center’s de-identified DNA biobank (BioVU) with an available echocardiogram, RV-PA coupling was calculated as the ratio of tricuspid annular plane systolic excursion (TAPSE) to estimated RV systolic pressure (RVSP). The association between three measures of obesity and RV-PA coupling was examined using 2-sample inverse variance weighted (IVW) meta-analysis, and MR-Egger to assess for pleiotropy. Genetic instruments for obesity were constructed using prior summary statistics for body mass index (BMI), waist circumference, and whole body fat mass. Results: Median age of cohort was 63, 54% female. Median and IQR of variables were as follows: TAPSE 2.0 [1.6, 2.4], RVSP 31 [25, 40], TAPSE/RVSP 0.6 [0.4, 0.8]. By 2-sample MR, we found a significant negative association between genetically determined waist circumference and RV-PA coupling (β=-0.34, p=0.004) (Figure). We found similar negative associations between RV-PA coupling and BMI (β=-0.41, p=0.01) and whole body fat mass (β=-0.55 p=0.005). Units for estimates were log change in outcome (TAPSE/RVSP) per change in exposure. Conclusions: Our findings suggest shared genetic architecture between measures of adiposity and RV-PA coupling, supporting the notion that pathophysiologic mechanisms underlying adiposity may be play a causal role in impaired RV-PA coupling.
Abstract 13786: Effectiveness of Ambulatory Pulmonary Artery Pressure-Guided Therapy in Reducing Readmissions in Patients With Heart Failure With Reduced Ejection Fraction versus Heart Failure With Preserved Ejection Fraction
Authors: Akshay Goel, Aaqib H Malik, Dhrubajyoti Bandyopadhyay, Rahul Gupta, Adrija Hajra, Alexandros Briasoulis, Wilbert S Aronow, Julio A Panza, Gregg Lanier
Journal: Circulation (2022)

Introduction: The cardio-microelectromechanical system (CardioMEMS) is an implantable pulmonary artery pressure monitoring device that aims to avoid decompensated heart failure (HF) admissions through hemodynamic-guided care. The aim of our study was to compare the impact of CardioMEMS implantation on hospital readmissions between HFrEF and HFpEF patients. Methods: Data from the National Readmission Database 2015 to 2019 were analyzed. International Classification of Diseases codes were used to identify patients hospitalized for HF and those with CardioMEMS implantation. The outcome of interest was the 30-day readmission rate. Multivariate logistic regression analysis was done to account for possible confounders. Results: We identified 3,801,661 admissions with a primary diagnosis of HF. Of these, 2,279,203 (59.95%) patients carried a diagnosis of HFrEF, while 1,522,458 (40.05%) had HFpEF. Patient characteristics are shown in the table. CardioMEMS was implanted in 1100 patients with HFrEF, and 297 patients with HFpEF. Among patients with HFrEF, those who received CardioMEMS implantation during the index admission had a significantly lower 30-day readmission rate compared to those who did not (16.4% vs 21.0%, adjusted odds ratio [OR] 0.74, 95% confidence interval [CI] 0.63-0.87, p &lt;0.01) (Figure). However, among HFpEF patients, there was no significant reduction in 30-day readmissions after CardioMEMS implantation (19.8% vs 20.7%, adjusted OR 0.95, 95% CI 0.72-1.27, p = 0.37) (Figure). CardioMEMS implantation was not associated with a higher rate of complications such as major bleeding, acute kidney injury, or stroke, in both HFrEF and HFpEF groups. Conclusions: Our findings suggest that ambulatory pulmonary artery pressure-guided therapy may be more effective in reducing HF readmissions in patients with HFrEF than in those with HFpEF. This may have significant clinical implication in appropriate patient selection for CardioMEMS implantation.
Abstract 13337: Left Atrial Ejection Fraction by Cardiac Magnetic Resonance Imaging as a Predictor of Adverse Outcomes in Patients With Advanced Ischemic Cardiomyopathy
Authors: Chris Anthony, Donna Salam, Nancy Obuchowski, Danah Al-Deiri, Mustafa Turkmani, Tom Kai Ming K Wang, Zoran B Popovic, Christopher Nguyen, Brian P Griffin, Scott D Flamm, Wai Hong W Tang, Deborah H Kwon
Journal: Circulation (2022)

Background: The prognostic significance of cardiac magnetic resonance (CMR) based left atrial ejection fraction (LAEF) is not well defined in the ischemic cardiomyopathy (ICM) cohort.We assess the additive effect of LAEF in a model to predict outcomes in patients with ICM. Methods: Patients with ICM, who underwent CMR between April 2001 and March 2019 were retrospectively included. Clinical characteristics and CMR parameters were collected and analyzed and LAEF was calculated in addition to myocardial infarct size (MIS) using late gadolinium enhancement (LGE) and CMR based mitral regurgitant fraction (MRF). The primary clinical endpoint was a composite of all-cause mortality and cardiac transplant. A multiple-variable Cox proportional hazards regression model which included established predictors of outcome was constructed, followed by the addition of LAEF. Four pre-specified interactions of LAEF with left ventricular end systolic volume index (LVESVi), MIS and mitral regurgitant fraction (MRF) were tested at a significance level of 0.05. RESULTS: LA functional data was measured in 718 patients. There were 416 deaths and/or transplants, with a median duration of follow up of 1763 days (4.8 years) The mean LA EF was 36 [2 ,74]. In univariate analysis, lower LAEF and higher LAVI were significant predictors of worse outcome, HR= 0.12, 95% CI [0.06, 0.25], p&lt;0.001; HR 1.008, (1.003-1.014) p = 0.003. After addition to the multivariable model, a normal LAEF was highly predictive of reduced risk, HR 0.24, (0.12, 0.48), p&lt;0.001. In the interaction between LAEF and MIS with MR Fraction, the highest risk was observed in patients with an LAEF &lt; 20% and an MIS of &gt; 30%, with MR Fraction of &gt;35%, HR of 3.2 (1.73-5.93), p= 0.009. The lowest risk was in patients with an LAEF of &gt;50% with an MIS of &lt;15 and MR Fraction of &lt;35%, HR 1.07 (0.81-1.42), p=0.009. Figure 1. CONCLUSION: Reduced LAEF is an important predictor of increased mortality in patients with ICM and additive to MIS and MR Fraction.
Abstract 13513: Favorable Neighborhood Walkability is Associated With Lower Burden of CV Risk Factors Among Patients Within an Integrated Health System: Houston Methodist CVD Learning Health System Registry
Authors: Omar M Makram, Nwabunie Nwana, Charlie Nicolas, Alan P Pan, Rakesh Gullapelli, BUDHADITYA BOSE, Kobina Hagan, Tarang Parekh, Tamer Yahya, Zulqarnain Javed, Kershaw Patel, Sadeer Al-Kindi, Garima Sharma, Stephen Jones, Miguel Cainzos, Jay E Maddock, Khurram Nasir
Journal: Circulation (2022)

Background: Optimizing modifiable cardiovascular risk factors is critical to achieving AHA’s 2020 Strategic Impact Goals. Neighborhood and urban factors with a supportive walkable environment can enhance physical activity and hence impact CVH across a wide range of populations. We assessed whether a more walkable environment is associated with CV risk factor burden irrespective of CVD burden among a large diverse population within an integrated health system. Methods: Cross-sectional study using data from 1.01 million patients aged 18+ years in the Houston Methodist Cardiovascular Disease Learning Health System Registry (2016-2021). Individuals lacking NW (177,674) &amp; BMI &lt;18.5 kg/m 2 (27,065) were excluded. Neighborhood walkability (NW) was defined using 2019 Walk Score. Patients were assigned to 1 of 4 NW categories ( Figure ). Study participants were classified as poor (&gt;3 CV risk factors), average (1-2 CV risk factors) or optimal (0 CV risk factors). Results: We included 901,860 patients (mean age 51.88, female 59%, NHB 15%, and 16% Hispanics), most of these (86%) resided in the 2 least walkable neighborhoods. Age-adjusted prevalence of CV risk factors was significantly lower among participants in most favorable walkable neighborhoods irrespective of CVD status ( Figure ). In adjusted analysis, favorable NW (somewhat/very walkable) vs unfavorable NW (car dependent) was associated with 2-fold odds for optimal vs poor CVD risk (OR 2.07 95%CI: 2.01-2.12) among those without CVD. Similar results were found in those with CVD (OR 1.58 95% CI:1.41-1.77). Conclusions: Our findings demonstrate favorable association between neighborhood walkability and the CVD risk factors burden in large population of about 1 million individuals. These robust findings support multilevel health system stakeholder engagements and investments in walkable neighborhoods as a viable tool for mitigating growing burden of modifiable CV risk factors.
Abstract 13192: The Influence of Posture and Steps on Daytime Ambulatory Blood Pressure
Authors: Bethany Barone Gibbs, Matthew F Muldoon, Molly B Conroy, Joshua L Paley, Subashan Perera
Journal: Circulation (2022)

Introduction: Ambulatory blood pressure (BP) monitoring (ABPM) provides data beyond clinic BP. Yet, free-living activity prior to measurements may add variability and obscure clinical interpretation. The influence of posture and ambulation on ABPM is unclear. Hypothesis: Posture and ambulation will partially explain variability in daytime ABPM. Methods: This study used baseline data from RESET BP (NCT03307343), a randomized clinical trial testing a sedentary behavior reduction intervention among inactive desk workers with elevated, unmedicated BP. ABPM was measured 2 x per self-reported waking hour over 24 hours with a SunTech Medical ® Oscar 2 TM ambulatory BP monitor. Upright posture and step count were concurrently captured with an activPAL TM thigh-worn accelerometer. Upright time and steps were summed for the 1-, 5-, 10-, and 15-minute intervals prior to each ABPM measurement. Percentage of BP variability explained (R 2 ) by upright time, steps, and both was calculated within-subject using linear regression. Additional models considered quadratic terms for upright time and steps. Results: Participants (n=256) were 59% female, with mean±SD age of 45.2±11.6 years, resting systolic BP (SBP) of 130±10 and diastolic BP (DBP) of 84±7, and provided 32.5±3.9 daytime ABPM measurements. Upright time and steps were directly associated with BP. Upright time and steps explained the most variability (highest R 2 ) using the 1-minute interval prior to ABPM measurement; R 2 gradually declined with increasing interval length. From 1-minute prior, upright time explained 12% of the variability in SBP and 10% of DBP, on average. Adding an upright time quadratic term increased R 2 (SBP: 16%; DBP: 13%). Steps in the minute prior explained 12% and 7% of the variability in SBP and DBP, respectively, and increased to 16% and 11% with the addition of a quadratic term. A final model including upright time, steps, and quadratic terms explained 25% and 20% of the variability in SBP and DBP, respectively. Conclusions: Posture and steps, especially in the minute prior, explained a substantial amount of individual variability in ABPM. These findings advance our understanding of BP variability and may have implications for the quantification and interpretation of daytime ABPM data.
Abstract 13661: An Adaptive Strategy of Predictive Enrichment to Increase Efficiency of Randomized Clinical Trials Using Machine Learning: <i>A Simulation of the IRIS Trial</i>
Authors: Evangelos K Oikonomou, Marc A Suchard, Walter N Kernan, Lawrence H Young, Silvio E Inzucchi, Rohan Khera
Journal: Circulation (2022)

Introduction: Randomized controlled trials (RCT) represent the cornerstone of evidence-based medicine but often carry high financial costs and lengthy time frames. Hypothesis: We hypothesized that a machine learning (ML) strategy of predictive enrichment can reduce the size of RCTs through adaptive enrollment based on projected response profiles. Methods: We conducted a post-hoc analysis of individual patient data from the Insulin Resistance Intervention after Stroke (IRIS) trial using dynamic computational trial phenomapping. After a study period of 36 months, we performed serial annual interim analyses ( A ). For this, we designed an algorithm that used a phenotypic trial representation using 59 baseline variables to predict personalized effects of pioglitazone on fatal/nonfatal stroke or myocardial infarction (study outcome). Compared with a complete trial enrollment (100%), in an adaptive fashion, we a priori restricted enrollment to two thirds (66.7%) of eligible participants between each interim analysis based on the projected treatment benefit. Since this was defined by their baseline phenotypic profile, treatment randomization was preserved. We employed these patient subsets as comparators and assessed the effect of pioglitazone on the study outcome through Cox regression models. Results: Compared to the unrestricted enrollment of participants ( blue line ), an ML-guided adaptive strategy of predictive enrichment ( green line ) was associated with defining the same treatment effect size with a lower trial size - 3876 vs 2946 participants ( B-C ). Both approaches appeared to meet statistical significance at 6 years after the trial onset ( D-E ). In contrast, a strategy of random patient selection ( orange line ) did not show significant benefit at the same population size. Conclusions: We developed an adaptive strategy for predictive enrichment to increase efficiency of RCTs using machine learning.